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Tag: eigenvalues

Data Analysis

Mean, Variance, Standard Deviation, Standard Score, Covariance & Data Projection

October 31, 2018October 17, 2020 1 Comment

Variance – It is the measure of squared difference from the Mean. To calculate it we follow certain steps mentioned below: Calculate average of numbers For each numbers subtract the mean and square the result Calculate the average of those squared differences i.e. Variance Editorial Team

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Data Analysis

Eigenvector represents greatest variance in case of PCA

October 31, 2018October 17, 2020 2 Comments

In case of Principal Component Analysis we project our data points on a vector in a direction of maximum variance to decrease the number of existing components. In this case we consider the direction eigenvector generated using covariance matrix as the direction of maximum variance. In this article we look into the proof of why […]

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Data Analysis

Eigen Vector and Eigen Values

October 30, 2018October 17, 2020 1 Comment

Eigen vector is the direction in a coordinate space defined by a metrics which doesn’t change its direction with metrics transformation. Eigen value is a scaler number which is multiplied with Eigen vector to give same result as Eigen vector multiplier with existing metrics. Editorial Team

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